Automatic Indexing and Retrieval of Large Broadcast News Video Collections – The TRECVID Experience

Author(s):  
Tat-Seng Chua
2020 ◽  
Vol 10 (9) ◽  
pp. 3172
Author(s):  
Diego Gragnaniello ◽  
Andrea Bottino ◽  
Sandro Cumani ◽  
Wonjoon Kim

Nowadays, deep learning is the fastest growing research field in machine learning and has a tremendous impact on a plethora of daily life applications, ranging from security and surveillance to autonomous driving, automatic indexing and retrieval of media content, text analysis, speech recognition, automatic translation, and many others [...]


2010 ◽  
Vol 43 (4) ◽  
pp. 623-631 ◽  
Author(s):  
Dympna M. O’Sullivan ◽  
Szymon A. Wilk ◽  
Wojtek J. Michalowski ◽  
Ken J. Farion

1998 ◽  
Author(s):  
Myung-Sup Yang ◽  
Cheol-Jung Yoo ◽  
Ok-Bae Chang

Author(s):  
Fan Jiang ◽  
Yu-Jin Zhang

This chapter addresses the tasks of providing the semantic structure and generating the abstraction of content in broadcast news. Based on extraction of two specific visual cues, Main Speaker Close-Up (MSC) and news caption, a hierarchy of news video index is automatically constructed for efficient access to multi-level contents. In addition, a unique MSC-based video abstraction is proposed to help satisfy the need for news preview and key-person highlighting. Experiments on news clips from MPEG-7 video content sets yield encouraging results that prove the efficiency of our video indexing and abstraction scheme.


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